Proactive headlight tracking for vehicle auto high beam assist

ABSTRACT

In exemplary embodiments, methods and systems are provided for controlling an auto high beam functionality for headlights of a vehicle. In an exemplary embodiment, a method includes: obtaining camera data pertaining to an object in front of the vehicle; identifying, via a processor, a radial gradient of pixels in a region of interest from the camera data; and automatically controlling, via the processor, the auto high beam functionality for the headlights based on the radial gradient.

INTRODUCTION

The technical field generally relates to the field of vehicles and, morespecifically, to controlling auto high beam functionality in vehicles.

Many vehicles today have headlights with automatic high beamfunctionality, for example in which the vehicle headlights' high beamsare automatically controlled under various circumstances. In suchvehicles, the high beams may be turned off when an approaching vehicleis detected. However, in certain situations, existing headlight autohigh beam control systems may not always be optimally controlled, forexample, when driving on a roadway with a hill or other incline.

Accordingly, it is desirable to provide improved systems and methods forcontrolling auto high beam functionality for vehicle headlights.Furthermore, other desirable features and characteristics of the presentinvention will become apparent from the subsequent detailed descriptionof the invention and the appended claims, taken in conjunction with theaccompanying drawings and this background of the invention.

SUMMARY

In an exemplary embodiment, a method is provided for controlling an autohigh beam functionality for headlights of a vehicle, the methodincluding: obtaining camera data pertaining to an object in front of thevehicle; identifying, via a processor, a radial gradient of pixels in aregion of interest from the camera data; and automatically controlling,via the processor, the auto high beam functionality for the headlightsbased on the radial gradient.

Also in an exemplary embodiment, the method further includes:calculating, via the processor, a size of the radial gradient from thecamera data; wherein the automatically controlling includesautomatically controlling, via the processor, the auto high beamfunctionality for the headlights based on the size of the radialgradient.

Also in an exemplary embodiment, the calculating of the size of theradial gradient includes calculating, via the processor, a number ofpixels in the radial gradient from the camera data; and theautomatically controlling includes automatically reducing, via theprocessor, an intensity of the headlights when the number of pixels inthe radial gradient exceeds a predetermined threshold.

Also in an exemplary embodiment, the method further includes:calculating, via the processor, a density of the radial gradient fromthe camera data; wherein the automatically controlling includesautomatically controlling, via the processor, the auto high beamfunctionality for the headlights based on the density of the radialgradient.

Also in an exemplary embodiment, the calculating of the density of theradial gradient includes calculating, via the processor, a differencebetween a maximum shade and a minimum shade in the radial gradient fromthe camera data; and the automatically controlling includesautomatically reducing, via the processor, an intensity of theheadlights if the difference between the maximum shade and the minimumshade in the radial gradient exceeds a predetermined threshold.

Also in an exemplary embodiment, the method further includes:calculating, via the processor, a size of the radial gradient from thecamera data; and calculating, via the processor, a density of the radialgradient from the camera data; wherein the automatically controllingincludes automatically controlling, via the processor, the auto highbeam functionality for the headlights based on both the size and thedensity of the radial gradient.

Also in an exemplary embodiment, the calculating of the size of theradial gradient includes calculating, via the processor, a number ofpixels in the radial gradient from the camera data; the calculating ofthe density of the radial gradient includes calculating, via theprocessor, a difference between a maximum shade and a minimum shade inthe radial gradient from the camera data; and the automaticallycontrolling includes automatically reducing, via the processor, anintensity of the headlights based on both the number of pixels and thedifference between the maximum shade and the minimum shade in the radialgradient from the camera data.

In another exemplary embodiment, a system for controlling an auto highbeam functionality for headlights of a vehicle, the system including: acamera configured to provide camera data pertaining to an object infront of the vehicle; and a processor coupled to the camera andconfigured to at least facilitate: identifying a radial gradient ofpixels in a region of interest from the camera data; and automaticallycontrolling the auto high beam functionality for the headlights based onthe radial gradient.

Also in an exemplary embodiment, the processor is further configured toat least facilitate: calculating a size of the radial gradient from thecamera data; and automatically controlling the auto high beamfunctionality for the headlights based on the size of the radialgradient.

Also in an exemplary embodiment, the processor is further configured toat least facilitate: calculating the size by calculating a number ofpixels in the radial gradient from the camera data; and automaticallyreducing an intensity of the headlights when the number of pixels in theradial gradient exceeds a predetermined threshold.

Also in an exemplary embodiment, the processor is further configured toat least facilitate: calculating a density of the radial gradient fromthe camera data; and automatically controlling, via the processor, theauto high beam functionality for the headlights based on the density ofthe radial gradient.

Also in an exemplary embodiment, the processor is further configured toat least facilitate: calculating the density by calculating a differencebetween a maximum shade and a minimum shade in the radial gradient fromthe camera data; and automatically reducing an intensity of theheadlights if the difference between the maximum shade and the minimumshade in the radial gradient exceeds a predetermined threshold.

Also in an exemplary embodiment, the processor is further configured toat least facilitate: calculating a size of the radial gradient from thecamera data; calculating a density of the radial gradient from thecamera data; and automatically controlling the auto high beamfunctionality for the headlights based on both the size and the densityof the radial gradient.

Also in an exemplary embodiment, the processor is further configured toat least facilitate: calculating the size by calculating a number ofpixels in the radial gradient from the camera data; calculating thedensity by calculating a difference between a maximum shade and aminimum shade in the radial gradient from the camera data; andautomatically reducing, via the processor, an intensity of theheadlights based on both the number of pixels and the difference betweenthe maximum shade and the minimum shade in the radial gradient from thecamera data.

In another exemplary embodiment, a vehicle is provided that includes:one or more headlights having an auto high beam functionality; and acontrol system for controlling the auto high beam functionality for theheadlights, the control system including: a camera configured to providecamera data pertaining to an object in front of the vehicle; and aprocessor coupled to the camera and configured to at least facilitate:identifying a radial gradient of pixels in a region of interest from thecamera data; and automatically controlling the auto high beamfunctionality for the headlights based on the radial gradient.

Also in an exemplary embodiment, the processor is further configured toat least facilitate: calculating a size of the radial gradient from thecamera data; and automatically controlling the auto high beamfunctionality for the headlights based on the size of the radialgradient.

Also in an exemplary embodiment, the processor is further configured toat least facilitate: calculating the size by calculating a number ofpixels in the radial gradient from the camera data; and automaticallyreducing an intensity of the headlights when the number of pixels in theradial gradient exceeds a predetermined threshold.

Also in an exemplary embodiment, wherein the processor is furtherconfigured to at least facilitate: calculating a density of the radialgradient from the camera data; and automatically controlling, via theprocessor, the auto high beam functionality for the headlights based onthe density of the radial gradient.

Also in an exemplary embodiment, the processor is further configured toat least facilitate: calculating the density by calculating a differencebetween a maximum shade and a minimum shade in the radial gradient fromthe camera data; an automatically reducing an intensity of theheadlights if the difference between the maximum shade and the minimumshade in the radial gradient exceeds a predetermined threshold

Also in an exemplary embodiment, the processor is further configured toat least facilitate: calculating a size of the radial gradient from thecamera data by calculating a number of pixels in the radial gradientfrom the camera data; calculating a density of the radial gradient fromthe camera data by calculating a difference between a maximum shade anda minimum shade in the radial gradient from the camera data; andautomatically reducing, via the processor, an intensity of theheadlights based on both the number of pixels and the difference betweenthe maximum shade and the minimum shade in the radial gradient from thecamera data.

DESCRIPTION OF THE DRAWINGS

The present disclosure will hereinafter be described in conjunction withthe following drawing figures, wherein like numerals denote likeelements, and wherein:

FIG. 1 is a functional block diagram of a vehicle that includes vehicleheadlights and a control system that controls the headlights, includingauto high beam functionality for the vehicle headlights, in accordancewith exemplary embodiments;

FIG. 2 is a functionality block diagram of a computer system of acontrol system for controlling headlights of a vehicle, including forcontrolling auto high beam functionality, and that can be implemented inconnection with the control system of FIG. 1, in accordance withexemplary embodiments;

FIG. 3 is a flowchart of a process for controlling auto high beamfunctionality for headlights of a vehicle, and that can be implementedin connection with the vehicle of FIG. 1, the control system of FIG. 1,and the computer system of FIG. 2, in accordance with exemplaryembodiments; and

FIGS. 4 and 5 are schematic diagrams of an illustrative example of animplementation of the process of FIG. 3 in connection with the vehicleof FIG. 1, as depicted on a roadway along with one or more othervehicles, in accordance with various exemplary embodiments.

DETAILED DESCRIPTION

The following detailed description is merely exemplary in nature and isnot intended to limit the disclosure or the application and usesthereof. Furthermore, there is no intention to be bound by any theorypresented in the preceding background or the following detaileddescription.

FIG. 1 illustrates a vehicle 100, according to an exemplary embodiment.As described in greater detail further below, the vehicle 100 includes acontrol system 102 for controlling auto high beam functionality forheadlights 104 of the vehicle 100. As described in greater detailfurther below, the control system 102 controls the high beamfunctionality of the headlights 104 based on a radial gradient in cameradata with respect to a region of interest for an object in front of thevehicle 100, in accordance with exemplary embodiments.

In certain embodiments, the vehicle 100 comprises an automobile. Invarious embodiments, the vehicle 100 may be any one of a number ofdifferent types of automobiles, such as, for example, a sedan, a wagon,a truck, or a sport utility vehicle (SUV), and may be two-wheel drive(2WD) (i.e., rear-wheel drive or front-wheel drive), four-wheel drive(4WD) or all-wheel drive (AWD), and/or various other types of vehiclesin certain embodiments. In certain embodiments, the vehicle 100 may alsocomprise a motorcycle and/or one or more other types of vehicles. Inaddition, in various embodiments, it will also be appreciated that thevehicle 100 may comprise any number of other types of mobile platforms.

In the depicted embodiment, the vehicle 100 includes a body 106 thatsubstantially encloses other components of the vehicle 100. Also in thedepicted embodiment, the vehicle 100 includes a plurality of axles andwheels (not depicted in FIG. 1) that facilitate movement of the vehicle100 as part of or along with a drive system 108 of the vehicle 100.

In various embodiments, the drive system 108 comprises a propulsionsystem. In certain exemplary embodiments, the drive system 108 comprisesan internal combustion engine and/or an electric motor/generator. Incertain embodiments, the drive system 108 may vary, and/or two or moredrive systems 108 may be used. By way of example, the vehicle 100 mayalso incorporate any one of, or combination of, a number of differenttypes of propulsion systems, such as, for example, a gasoline or dieselfueled combustion engine, a “flex fuel vehicle” (FFV) engine (i.e.,using a mixture of gasoline and alcohol), a gaseous compound (e.g.,hydrogen and/or natural gas) fueled engine, a combustion/electric motorhybrid engine, and an electric motor.

As depicted in FIG. 1, in various embodiments the control system 102includes one or more of the following: a vision system (FOM) 112, aninstrument panel cluster (IPC) 116, a body control module (BCM) 118, andan exterior lighting module (ELM). In various embodiments, the visionsystem 112 obtains camera data for the vehicle 100, identifies andperforms calculations with respect to a radial gradient with respect toa region of interest in the camera data that corresponds to an object infront of the vehicle 100 (including calculations as to a size and adensity of the radial gradient), and provides instructions forcontrolling auto high beam functionality for the headlights 104 of thevehicle 100.

In various embodiments, the vision system 112 provides these featuresvia machine vision and image processing 114 with respect to the cameradata and the identified radial gradient therein. In addition, in variousembodiments, the vision system 112 controls the auto high beamfunctionality for the headlights 104 via instructions that are providedfrom the vision system 112 through the body control module 118 and on tothe exterior lighting module 120 that is coupled to the headlights 104.In various embodiments, these steps are set forth in greater detailfurther below in connection with the process 300 of FIG. 3 and theimplementations of FIGS. 4 and 5.

Also in various embodiments, the body control module 118 also uses otherdata, calculations, and requirements for controlling the auto high beamfunctionality for the headlights 104 via instructions provided to theexterior lighting module 120, for example, using other data, such asvehicle speed as well as user inputs (e.g. user instructions and/oroverrides) from the instrument panel cluster 116.

With respect to FIG. 2, a functional block diagram is provided for acontrol system 200 that controls auto high beam functionality forheadlights for a vehicle, in accordance with exemplary embodiments. Invarious embodiments, the control system 200 corresponds to the controlsystem 102 of the vehicle 100 of FIG. 1, and/or components thereof. Incertain embodiments, the control system 200 and/or components thereofare part of the vision system 112 of FIG. 1. In certain embodiments, thecontrol system 200 and/or components thereof may be part of and/orcoupled to one or more of the vision system 112, instrument panelcluster 116, body control module 118, and/or exterior lighting module120. In addition, while FIG. 2 depicts a control system 200 having asensor array 202 (with a camera 212 and other sensors) and a computersystem 204 (with a processor 222, a memory 224, and other components),and while the control system 200 in one embodiment corresponds at leastin part with the vision system 112 of FIG. 1, it will be appreciatedthat in various embodiments each of the vision system 112, instrumentcluster 116, body control module 118, and exterior lighting module 120may include the same or similar components as set forth in FIG. 2 and/oras described below, for example including respective sensors and/orrespective processors and memories, and so on.

As depicted in FIG. 2, in various embodiments, the control system 200incudes a sensor array 202 and a controller 204. In various embodiments,the sensor array 202 includes one or more cameras 212. In variousembodiments, one or more of the cameras 212 face in front of the vehicle100, for example in order to detect objects on or near a roadway or pathin front of the vehicle 100. Also in certain embodiments, the sensorarray 202 may also include one or more other types of detection sensors2014 (e.g., including, in some embodiments, RADAR, LiDAR, SONAR, or thelike), one or more vehicle speed sensors 216 (e.g., wheel speed sensors,accelerometers, and/or other sensors for measuring data for determininga speed of the vehicle 100), and/or one or more other sensors 218 (e.g.,in certain embodiments, user input sensors, GPS sensors, and so on).

Also as depicted in FIG. 2, the controller is coupled to the sensorarray 202. In various embodiments, the controller 204 controls auto highbeam functionality for the headlights of the vehicle, based on anidentified radial grant from camera data from the camera 212 pertainingto one or more detected objects in front of the vehicle (e.g., along apath or roadway in front of the vehicle), for as set forth in greaterdetail further below in connection with the process 300 of FIG. 3 andthe implementations of FIGS. 4 and 5. As depicted in FIG. 2, in variousembodiments, the controller 204 comprises a computer system comprising aprocessor 222, a memory 224, an interface, a storage device 228, a bus230, and a disk 236.

As depicted in FIG. 2, the controller 204 comprises a computer system.In certain embodiments, the controller 204 may also include the sensorarray 202 and/or one or more other vehicle components. In addition, itwill be appreciated that the controller 204 may otherwise differ fromthe embodiment depicted in FIG. 2. For example, the controller 204 maybe coupled to or may otherwise utilize one or more remote computersystems and/or other control systems, for example as part of one or moreof the above-identified vehicle devices and systems.

In the depicted embodiment, the computer system of the controller 204includes a processor 222, a memory 224, an interface 226, a storagedevice 228, and a bus 230. The processor 222 performs the computationand control functions of the controller 204, and may comprise any typeof processor or multiple processors, single integrated circuits such asa microprocessor, or any suitable number of integrated circuit devicesand/or circuit boards working in cooperation to accomplish the functionsof a processing unit. During operation, the processor 222 executes oneor more programs 232 contained within the memory 224 and, as such,controls the general operation of the controller 204 and the computersystem of the controller 204, generally in executing the processesdescribed herein, such as the process 300 discussed further below inconnection with FIG. 2.

The memory 224 can be any type of suitable memory. For example, thememory 224 may include various types of dynamic random access memory(DRAM) such as SDRAM, the various types of static RAM (SRAM), and thevarious types of non-volatile memory (PROM, EPROM, and flash). Incertain examples, the memory 224 is located on and/or co-located on thesame computer chip as the processor 222. In the depicted embodiment, thememory 224 stores the above-referenced program 232 along with one ormore stored values 234 (e.g., including, in various embodiments,predetermined threshold values for controlling the auto high beamfunctionality).

The bus 230 serves to transmit programs, data, status and otherinformation or signals between the various components of the computersystem of the controller 204. The interface 226 allows communications tothe computer system of the controller 204, for example from a systemdriver and/or another computer system, and can be implemented using anysuitable method and apparatus. In one embodiment, the interface 226obtains the various data from the sensor array 202, the drive system108, the suspension system 106, and/or one or more other componentsand/or systems of the vehicle 100. The interface 226 can include one ormore network interfaces to communicate with other systems or components.The interface 226 may also include one or more network interfaces tocommunicate with technicians, and/or one or more storage interfaces toconnect to storage apparatuses, such as the storage device 228.

The storage device 228 can be any suitable type of storage apparatus,including various different types of direct access storage and/or othermemory devices. In one exemplary embodiment, the storage device 228comprises a program product from which memory 224 can receive a program232 that executes one or more embodiments of one or more processes ofthe present disclosure, such as the steps of the process 300 discussedfurther below in connection with FIG. 2. In another exemplaryembodiment, the program product may be directly stored in and/orotherwise accessed by the memory 224 and/or one or more other disks 236and/or other memory devices.

The bus 230 can be any suitable physical or logical means of connectingcomputer systems and components. This includes, but is not limited to,direct hard-wired connections, fiber optics, infrared and wireless bustechnologies. During operation, the program 232 is stored in the memory224 and executed by the processor 222.

It will be appreciated that while this exemplary embodiment is describedin the context of a fully functioning computer system, those skilled inthe art will recognize that the mechanisms of the present disclosure arecapable of being distributed as a program product with one or more typesof non-transitory computer-readable signal bearing media used to storethe program and the instructions thereof and carry out the distributionthereof, such as a non-transitory computer readable medium bearing theprogram and containing computer instructions stored therein for causinga computer processor (such as the processor 222) to perform and executethe program. Such a program product may take a variety of forms, and thepresent disclosure applies equally regardless of the particular type ofcomputer-readable signal bearing media used to carry out thedistribution. Examples of signal bearing media include: recordable mediasuch as floppy disks, hard drives, memory cards and optical disks, andtransmission media such as digital and analog communication links. Itwill be appreciated that cloud-based storage and/or other techniques mayalso be utilized in certain embodiments. It will similarly beappreciated that the computer system of the controller 204 may alsootherwise differ from the embodiment depicted in FIG. 2, for example inthat the computer system of the controller 204 may be coupled to or mayotherwise utilize one or more remote computer systems and/or othercontrol systems.

FIG. 3 is a flowchart of a process 300 for controlling high beamfunctionality for headlights of a vehicle, in accordance with exemplaryembodiments. In various embodiments, the process 300 may be implementedin connection with the vehicle 100 of FIG. 1, including the controlsystem 102 thereof, and including the control system 200 of FIG. 2(and/or components thereof). The process 300 is also described furtherbelow in connection with FIGS. 4 and 5, which provide illustrativeexamples of an implementation of the process 300 of FIG. 3 in connectionwith the vehicle 100 of FIG. 1, as depicted on a roadway with othervehicles in front of the vehicle 100, in accordance with variousexemplary embodiments.

As depicted in FIG. 3, in various embodiments the process 300 begins at302. In various embodiments, the process 300 begins when one or moreevents occur to indicate that a vehicle drive is taking place or aboutto take place, such as a driver, operator, or passenger entering thevehicle 100, an engine or motor of the vehicle 100 being turned on, atransmission of the vehicle 100 being placed in a “drive” mode, or thelike.

Sensor data is collected at 303. In various embodiments, camera data isobtained from the one or more cameras 212 of FIG. 2, including cameradata with images of a path or roadway, and any detected objects thereinor in proximity thereto, in front of the vehicle 100 (i.e., in thedirection in which the vehicle 100 is travelling) In certainembodiments, additional sensor data may also be obtained from one ormore other sensors of the sensor array 202 of FIG. 2, for exampleincluding other types of sensor data from other detection sensors 214 toidentify objects in front of the vehicle 100 (e.g., using RADAR, LiDAR,SONAR, or the like) and/or vehicle speed (e.g., via one or more speedsensors 216 and/or other vehicle data.

In various embodiments, an image frame is obtained, at 304, from thecamera data. In various embodiments, each image frame corresponds tocamera data for regions in front of the vehicle 100 at a particularpoint in time.

Also in various embodiments, the horizontal field of view (HFOV) andvertical field of view (VFOV) are calibrated at 306 using the sensordata. In various embodiments, the HFOV and VFOV are calibrated by theprocessor 222 of FIG. 2 using the sensor data 303. Also in variousembodiments, the region of interest (ROI) in 308 can only be preciselyidentified after the exact calibration of the HFOV and VFOV.

In various embodiments, a region of interest is identified at 308. Invarious embodiments, the region of interest (ROI) is identified by theprocessor 222 of FIG. 2 as a region of the frame from the camera datasurrounding a detected object in front of the vehicle 100 (e.g., on ornear a path or roadway in front of the vehicle 100), based on thehorizontal and vertical field of view. In various embodiments, furtherprocessing is then confined to this particular region of the imageframe.

A radial gradient is identified for the image frame at 310. In variousembodiments, the processor 222 of FIG. 2 identifies a radial gradientwithin the region of interest of 308 as an area of transition throughmultiple levels of lightness to darkness (or vice versa) within theregion of interest of the image frame. In various embodiments, thepixels of the region of interest are scanned via the processor 222 inorder to identify a gradient.

For example, with reference to FIG. 4, a first implementation isprovided, showing a first image frame 400 including a detected objectthat is along a roadway in front of the vehicle 100 (not depicted inFIG. 4). As shown in FIG. 4, the first image frame 400 includes a radialgradient 402 surrounding headlights of the detected object (i.e., adetected oncoming vehicle). As shown in FIG. 4, in this example, theradial gradient 402 extends from a center 404 to an outer rim 406. Alsoas shown in FIG. 4, the radial gradient 402 exemplifies a transitionbetween a lightest region in the center 404, a darkest region in theouter rim 406, and various different shades (e.g., different shades ofgrey) that are each incrementally darker from one another from thecenter 404 to the outer rim 406.

With reference back to FIG. 3, in various embodiments, a size of theradial gradient is calculated and monitored at 312. In variousembodiments, the size of the radial gradient comprises a count of thenumber of pixels in the gradient, and/or in a component region therein.For example, in one embodiment, the size of the radial gradientcomprises a count of pixels from the center 404 to a single outer cornerof the outer rim 406 (e.g., corresponding to a radius of the radialgradient 402). By way of additional example, in certain otherembodiments, the size of the radial gradient comprises a count of pixelsthroughout the entire surface of the outer rim 406 (e.g., correspondingto an area of the radial gradient 402).

Also in various embodiments, a density of the radial gradient iscalculated and monitored at 314. In various embodiments, the density ofthe radial gradient comprises a difference between the minimum andmaximum shades in the radial gradient.

In various embodiments, a determination is made at 316 as to whether thesize of the radial gradient is greater than a predetermined threshold.In various embodiments, the processor 222 of FIG. 2 makes adetermination as to whether the number of pixels in the radial gradient,as counted at 312, exceeds a predetermined threshold. In variousembodiments, the threshold is also a calibratable look up tablecomprising of both radius counts and area counts. Also in variousembodiments, if it is determined that the size of the radial gradient isgreater than the predetermined threshold, then the process proceeds tostep 320, described further below. Also in various embodiments,otherwise the process proceeds to the above-described step 310.

In various embodiments, a determination is made at 318 as to whether thedensity of the radial gradient is greater than a predeterminedthreshold. In various embodiments, the processor 222 of FIG. 2 makes adetermination as to whether the difference between the minimum andmaximum color shades of the pixels number of pixels in the radialgradient, as determined at 314, exceeds a predetermined threshold. Invarious embodiments, the density threshold is also a calibratable lookup table comprising exponential/linear/logarithmic increase in thedensity counts. In various embodiments, if it is determined that thedensity of the radial gradient is greater than the predeterminedthreshold, then the process proceeds to step 320, described furtherbelow. Also in various embodiments, otherwise the process proceeds tothe above-described step 310.

With respect to steps 316 and 318, in certain embodiments, the processproceeds to step 320 if both the size and the density of the radialgradient exceed their respective thresholds (and otherwise returns tostep 310). In contrast, in certain other embodiments, the processproceeds to step 320 if either the size, or the density, or both, aregreater than their respective predetermined thresholds (and otherwisereturns to step 310).

During step 320, a gradient index is assigned. In various embodiments,the processor 222 of FIG. 2 assigns an index value representing ageographic location of the radial gradient. In addition, in certainembodiments, an intensity of the auto high beams for the headlights arereduced at 322, specifically by instructions provided by the processor222 of FIG. 2 (e.g., as transmitted via the vision system 112 throughthe body control module 118 to the exterior lighting module 120 of FIG.1). In addition, also in certain embodiments, the process proceeds tostep 323, described below.

During step 322, a scan is performed of possible headlights within theradial gradient, and a determination is made as to whether headlights ofanother vehicle have been identified in the radial gradient. In certainembodiments, step 322 includes a determination made by the processor 222of FIG. 2 as to whether a closer inspection of the camera data (i.e., ina future frame as the detected object comes closer to the vehicle 100)reveals that headlights of another vehicle are indeed represented by theradial gradient.

For example, with respect to FIG. 5, a second image frame 500 isprovided, that is subsequent in time to the first image frame 400 ofFIG. 4. As shown in FIG. 5, as the detected object comes closer to thevehicle 100 of FIG. 1, the subsequent (second) image frame 500 revealsthat two headlights 502 are present from another vehicle 100 in thesecond image frame. In various embodiments, this serves as aconfirmation of the initial determination (that was based on the radialgradient) that another vehicle is approaching the vehicle 100 of FIG. 1.

With reference back to FIG. 3, in various embodiments, if it isdetermined that headlights of another vehicle are not found as beingrepresented within the radial gradient, then the auto high beamfunctionality is turned on (or turned back on) for the headlights 104 ofthe vehicle 100 at 324. In various embodiments, the process then returnsto 304.

Conversely, in various embodiments, if it is determined that headlightsof another vehicle are found as being represented within the radialgradient, then the process begins tracking the other vehicle at 326(e.g., via instructions provided by the processor 222 to the sensorarray 202 of FIG. 2), and the automatic high beams are turned off at 328by instructions provided by the processor 222 of FIG. 2 (e.g., astransmitted via the vision system 112 through the body control module118 to the exterior lighting module 120 of FIG. 1).

Also in various embodiments, a headlight index is assigned for theheadlights of the other vehicle (e.g., pertaining to a geographiclocation thereof) at 330, and two dimensional coordinates calculatedfrom image area are provided for the headlights of the other vehicle at332, based on the physical vehicle's geographic location. In addition,in various embodiments, the two-dimensional coordinates are transformedto latitudinal and longitudinal values using intrinsic values at 334.

In certain embodiments, auto high beams are partially turned off at 336.For example, in certain embodiments, certain of the high beams that arefacing toward the additional vehicle of FIG. 5 may be turned off at 336,whereas other high beams that are not facing toward the additionalvehicle of FIG. 5 may remain on high beam mode at 336. In variousembodiments, such instructions are provided via the processor 222 ofFIG. 2 (e.g., as transmitted via the vision system 112 through the bodycontrol module 118 to the exterior lighting module 120 of FIG. 1). Alsoin certain embodiments, tracking of the additional vehicle continues invarious iterations of step 326 until the additional vehicle is no longerpresent in the camera data image frames, after which the process returnsto step 304 with respect to the detection of a new object.

Accordingly, methods, systems, and vehicles are provided for controllingauto (or automatic) high beam functionality for headlights of vehicles.In various embodiments, camera data is utilized to detect and examine aradial gradient in the camera images from headlights of a detectedvehicle that is in front of the vehicle 100 of FIG. 1, for use incontrolling the auto high beam functionality. In various embodiments,the auto high beams are reduced or turned off when the radial gradientindicates that another vehicle is present in front of the vehicle 100,to thereby reduce glare for the other vehicle. By using the radialgradient, the disclosed processes, systems, and vehicles can potentiallyprovide earlier detection of an approaching vehicle, particularly insituations in which there is a hill and/or sloped road, thereby furtherminimizing glare for the driver of the approaching vehicle.

It will be appreciated that the systems, vehicles, applications, andimplementations may vary from those depicted in the Figures anddescribed herein. For example, in various embodiments, the vehicle 100,the control system 102, components thereof, and/or other components maydiffer from those depicted in FIG. 1 and/or described above inconnection therewith. It will also be appreciated that components of thecontrol system 200 of FIG. 2 may differ in various embodiments. It willfurther be appreciated that the steps of the process 300 may differ,and/or that various steps thereof may be performed simultaneously and/orin a different order, than those depicted in FIG. 3 and/or describedabove. It will also be appreciated that implementations of the process300 may differ from those depicted in FIGS. 4 and/or 5 and/or asdescribed above.

While at least one exemplary embodiment has been presented in theforegoing detailed description, it should be appreciated that a vastnumber of variations exist. It should also be appreciated that theexemplary embodiment or exemplary embodiments are only examples, and arenot intended to limit the scope, applicability, or configuration of thedisclosure in any way. Rather, the foregoing detailed description willprovide those skilled in the art with a convenient road map forimplementing the exemplary embodiment or exemplary embodiments. Itshould be understood that various changes can be made in the functionand arrangement of elements without departing from the scope of thedisclosure as set forth in the appended claims and the legal equivalentsthereof

What is claimed is:
 1. A method for controlling an auto high beamfunctionality for headlights of a vehicle, the method comprising:obtaining camera data pertaining to an object in front of the vehicle;identifying, via a processor, a radial gradient of pixels in a region ofinterest from the camera data; calculating, via the processor, a densityof the radial gradient from the camera data by calculating a differencebetween a maximum shade and a minimum shade in the radial gradient fromthe camera data; and automatically controlling, via the processor, theauto high beam functionality for the headlights based on the density ofthe radial gradient, by automatically reducing an intensity of theheadlights if the difference between the maximum shade and the minimumshade in the radial gradient exceeds a predetermined threshold.
 2. Themethod of claim 1, further comprising: calculating, via the processor, asize of the radial gradient from the camera data; wherein theautomatically controlling further comprises automatically controlling,via the processor, the auto high beam functionality for the headlightsbased on the size of the radial gradient.
 3. The method of claim 2,wherein: the calculating of the size of the radial gradient comprisescalculating, via the processor, a number of pixels in the radialgradient from the camera data; and the automatically controlling furthercomprises automatically reducing, via the processor, an intensity of theheadlights when the number of pixels in the radial gradient exceeds apredetermined threshold.
 4. The method of claim 1, further comprising:calculating, via the processor, a size of the radial gradient from thecamera data; wherein the automatically controlling further comprisesautomatically controlling, via the processor, the auto high beamfunctionality for the headlights based on both the size and the densityof the radial gradient.
 5. The method of claim 4, wherein: thecalculating of the size of the radial gradient comprises calculating,via the processor, a number of pixels in the radial gradient from thecamera data; and the automatically controlling further comprisesautomatically reducing, via the processor, the intensity of theheadlights based on both the number of pixels and the difference betweenthe maximum shade and the minimum shade in the radial gradient from thecamera data.
 6. A system for controlling an auto high beam functionalityfor headlights of a vehicle, the system comprising: a camera configuredto provide camera data pertaining to an object in front of the vehicle;and a processor coupled to the camera and configured to at leastfacilitate: identifying a radial gradient of pixels in a region ofinterest from the camera data; calculating a size of the radial gradientby calculating a number of pixels in the radial gradient from the cameradata; calculating a density of the radial gradient by calculating adifference between a maximum shade and a minimum shade in the radialgradient from the camera data; and automatically controlling the autohigh beam functionality for the headlights based on the radial gradient,based on both the size and the density of the radial gradient, byautomatically reducing an intensity of the headlights based on both thenumber of pixels and the difference between the maximum shade and theminimum shade in the radial gradient from the camera data.
 7. The systemof claim 6, wherein the processor is further configured to at leastfacilitate: automatically reducing the intensity of the headlights whenthe number of pixels in the radial gradient exceeds a predeterminedthreshold.
 8. The system of claim 6, wherein the processor is furtherconfigured to at least facilitate: automatically reducing the intensityof the headlights if the difference between the maximum shade and theminimum shade in the radial gradient exceeds a predetermined threshold.9. A vehicle comprising: one or more headlights having an auto high beamfunctionality; and a control system for controlling the auto high beamfunctionality for the headlights, the control system comprising: acamera configured to provide camera data pertaining to an object infront of the vehicle; and a processor coupled to the camera andconfigured to at least facilitate: identifying a radial gradient ofpixels in a region of interest from the camera data; calculating a sizeof the radial gradient from the camera data by calculating a number ofpixels in the radial gradient from the camera data; calculating adensity of the radial gradient from the camera data by calculating adifference between a maximum shade and a minimum shade in the radialgradient from the camera data; and automatically controlling the autohigh beam functionality for the headlights based on the radial gradientby automatically reducing an intensity of the headlights based on boththe number of pixels and the difference between the maximum shade andthe minimum shade in the radial gradient from the camera data.
 10. Thevehicle of claim 9, wherein the processor is further configured to atleast facilitate: automatically reducing the intensity of the headlightswhen the number of pixels in the radial gradient exceeds a predeterminedthreshold.
 11. The vehicle of claim 9, wherein the processor is furtherconfigured to at least facilitate: automatically reducing an intensityof the headlights if the difference between the maximum shade and theminimum shade in the radial gradient exceeds a predetermined threshold.